Anti-collision monitoring system for tower crane based on CAN bus and multi-sensor fusion

Abstract

The application discloses a tower crane anti-collision monitoring system and control method based on CAN bus and multi-sensor fusion, which comprises a sensing module for collecting data, a control module for receiving sensing data output by the sensing module, a communication module for providing multi-tower coordination data support for logical judgment of the control module, and an execution module for receiving control instructions output by the control module. The control module adopts a double-controller coordination architecture, comprising a digital signal processor (DSP) for motor drive control of the tower crane, and a logic controller (PLC) for sensing data collection, multi-sensor fusion anti-collision method operation and collision risk logical judgment. The multi-sensor fusion anti-collision method dynamically corrects a preset anti-collision safety distance threshold according to environmental sensing data. The PLC controller also outputs control instructions to the execution module and simultaneously interacts relevant data to the communication module.

Description

Technical Field

[0001] This invention belongs to the field of tower crane safety monitoring and intelligent control technology, and more specifically, relates to a tower crane anti-collision monitoring system and its control method based on CAN bus and multi-sensor fusion. Background Technology

[0002] With the continuous expansion of construction projects, tower cranes have become the core lifting equipment for high-rise and super high-rise building construction, and their operational safety is directly related to the life and property safety of personnel on construction sites. Currently, multi-tower overlapping operations are increasingly common on construction sites, significantly increasing the risk of collisions between tower cranes, and between tower cranes and surrounding buildings or temporary facilities. Traditional collision avoidance monitoring methods are no longer sufficient to meet the safety requirements under complex working conditions.

[0003] Existing tower crane collision avoidance monitoring systems largely rely on single sensors or manual observation, resulting in limitations such as limited sensing dimensions and poor environmental adaptability. For example, relying solely on distance sensors cannot fully account for the impact of environmental factors like wind speed and tower tilt on safe distances. Under conditions of strong winds or abnormal tower posture, insufficient safe distances or delayed warnings are likely to occur. Furthermore, in multi-tower collaborative operations, the operating states of each tower crane are independent, lacking an efficient data exchange mechanism. This hinders cross-equipment risk prediction and collaborative protection, further increasing the probability of collision accidents.

[0004] Furthermore, existing collision avoidance systems mostly use fixed safety distance thresholds without dynamically adjusting to real-time environmental parameters. This can lead to unnecessary operational restrictions under mild conditions and insufficient safety redundancy under severe conditions. While some systems attempt to incorporate multi-source data, their complex computational logic and high response latency make them difficult to adapt to the dynamic characteristics of real-time tower crane operations. These issues prevent existing technologies from effectively improving the reliability and foresight of tower crane collision avoidance while ensuring operational efficiency, thus hindering further improvements in construction safety management.

[0005] Therefore, in order to address the practical problems existing in tower crane collision avoidance monitoring, such as insufficient perception dimensions, weak environmental adaptability, lack of multi-tower collaboration, and lack of dynamic adjustment capability of safety distance, it is of great engineering significance to develop an efficient and reliable multi-sensor fusion collision avoidance monitoring system to improve the safety of tower crane operation and reduce the risk of construction accidents. Summary of the Invention

[0006] This invention aims to solve the problems of existing tower crane collision avoidance monitoring, such as single sensing dimension, poor environmental adaptability, lack of multi-tower collaborative data, and fixed safety distance. It provides a collision avoidance monitoring system based on CAN bus and multi-sensor fusion. Through dual controller architecture, dynamic safety distance correction, and multi-tower data interaction, it improves the accuracy, foresight, and operational safety of collision avoidance monitoring.

[0007] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion, characterized in that it includes: A sensing module for collecting tower crane operating status data and external environment data; a control module for receiving sensor data output from the sensing module; a communication module for providing multi-tower collaborative data support for the control module's logical judgments; and an execution module for receiving control commands output from the control module and executing corresponding anti-collision actions according to the commands. The control module adopts a dual-controller collaborative architecture, including a digital signal processor (DSP) for driving control of the tower crane motor, and a logic controller (PLC) for sensor data acquisition, multi-sensor fusion collision avoidance method calculation, and collision risk logic judgment. The multi-sensor fusion collision avoidance method dynamically corrects the preset collision avoidance safety distance threshold based on environmental sensor data. The PLC controller also outputs control commands to the execution module and interacts with relevant data to the communication module.

[0008] Furthermore, the sensing module includes a rotary encoder for detecting the boom rotation angle, an ultrasonic sensor for detecting the distance to obstacles, a dual-axis tilt sensor for monitoring tower stability, a weight sensor for monitoring load weight, and a wind speed sensor for monitoring ambient wind speed. The rotary encoder is installed on the slewing mechanism, the ultrasonic sensor is installed at the end of the boom, the dual-axis tilt sensor is installed on the standard section of the tower body, the weight sensor is installed at the fixed end of the hoisting rope, and the wind speed sensor is installed at the top of the tower cap.

[0009] Furthermore, the communication module is a distributed communication network based on the CAN bus, and the control modules of each tower crane are mounted on the bus as independent nodes to complete real-time data exchange, including the operating status of the tower cranes and collision risks between the nodes.

[0010] Furthermore, the distributed communication network adopts a decentralized multi-master communication mode: any control node in the network has the ability to independently calculate collision risks. When a node detects an impending collision risk, it has the authority to send the highest priority emergency braking frame to the bus, and this process does not depend on the forwarding of the host computer monitoring module.

[0011] Furthermore, the execution module includes a frequency converter for adjusting the operating speed of the crane boom, a contactor for controlling the power supply to the mechanism, and an audible and visual alarm for issuing a collision warning.

[0012] Furthermore, the logic controller PLC receives signals from remote sensors through differential input ports and uses differential amplification principles to suppress high-frequency common-mode interference generated by field frequency converters and high-power motors.

[0013] Furthermore, the collision avoidance monitoring system is equipped with a three-level risk response mechanism: Warning level: When the distance to an obstacle enters the first preset range, an audible and visual alarm is triggered; Intervention level: When the distance to an obstacle enters the second preset range, or when the ambient wind speed or tower tilt angle reaches a set threshold, the system limits the operating speed of the crane boom and plans an avoidance path based on a multi-sensor fusion collision avoidance method; Hazard level: When the distance to the obstacle is less than the minimum safe distance, or the environmental parameters exceed the limit threshold, immediately cut off the power supply to the mechanism moving in the dangerous direction and implement forced braking.

[0014] Furthermore, the digital signal processor (DSP) integrates an orthogonal coded pulse (QEP) unit; the orthogonal coded pulse (QEP) unit is a pulse signal acquisition unit used to directly read the orthogonal pulse signal of the rotary encoder and complete the high-precision acquisition of the slewing angle of the tower crane boom.

[0015] Furthermore, the multi-sensor fusion collision avoidance method specifically includes: The minimum safe distance method is used for collision avoidance logic calculation, and the minimum safe distance of the tower crane foundation is preset when there is no environmental interference. Set the critical wind speed value Critical value of tower tilt angle ; The sensing module collects data at a fixed cycle. Continuously collect real-time relative position and distance between the tower crane and obstacles Real-time wind speed values Real-time tilt angle of the tower ,in This is the current data collection time; Linear prediction calculations are performed on the wind speed values ​​from three consecutive data acquisition cycles to obtain the predicted wind speed value for the next data acquisition cycle. , Linear prediction calculations are performed on the tower tilt angle for three consecutive acquisition cycles to obtain the predicted tilt angle for the next acquisition cycle. , ; Wind speed correction factor is set based on predicted wind speed value. Set the tilt correction factor based on the predicted tilt angle. ,when hour It shows an increasing change, when hour It shows an increasing change, when hour For a fixed reference value, when hour For fixed reference values; By fusing the real-time relative position distance with correction factors for predicted environmental parameters, the real-time minimum safe distance for tower cranes is calculated. , ; The logic controller PLC will display the relative position and distance in real time. With real-time minimum safe distance Perform real-time comparisons and output corresponding anti-collision control commands to the execution module based on the comparison results; in, The wind speed value collected by the sensing module in the previous collection cycle. The tower tilt angle was collected by the sensing module in the previous data collection cycle. For the ultrasonic sensor in the sensing module The real-time relative position and distance between the tower crane and the obstacle are constantly monitored.

[0016] As a second aspect of the present invention, a tower crane collision avoidance monitoring method based on CAN bus and multi-sensor fusion is also provided, applied to a tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion as described in any one of the claims, comprising: S1. The sensing module continuously collects the tower crane's operating status data and external environment data at a fixed collection cycle, including the real-time relative position distance between the tower crane and obstacles, the real-time wind speed value, and the real-time tilt angle of the tower body, and outputs the collected data to the control module. S2. Based on the collected data, the control module performs linear predictions on the wind speed and tower tilt angle for multiple consecutive collection cycles to obtain the predicted wind speed and tilt angle for the next collection cycle; based on the prediction results, wind speed correction factors and tilt angle correction factors are set and fused to obtain the real-time minimum safe distance. S3. The control module compares the real-time relative position distance with the real-time minimum safe distance, generates corresponding anti-collision control commands based on the comparison results, and outputs the control commands to the execution module. At the same time, the relevant operating status and risk data are exchanged with the control modules of other tower cranes through the communication module. S4. The execution module receives control commands and performs corresponding anti-collision actions, including adjusting the crane boom's running speed, controlling the power supply of the control mechanism, and issuing collision warning prompts.

[0017] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: 1. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion of the present invention collects multi-dimensional data on the tower crane's operating status and external environment through a sensing module, including parameters such as boom slewing angle, obstacle distance, tower tilt angle, load, and ambient wind speed, providing a comprehensive and reliable data foundation for collision avoidance decisions. This module uniformly outputs data from various sensors to the control module, avoiding the limitations of single-sensor data. Simultaneously, a fixed acquisition cycle ensures the real-time and continuous nature of the data, providing stable input support for subsequent predictive calculations and logical judgments, effectively improving the sensing accuracy and coverage of collision avoidance monitoring.

[0018] 2. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion of the present invention achieves separate execution of motor drive control and collision avoidance logic operation through a dual-controller collaborative architecture in the control module. The digital signal processor is responsible for high-precision motor drive and angle acquisition, while the logic controller focuses on sensor data processing and multi-sensor fusion collision avoidance method calculation. This module linearly predicts wind speed and tower tilt angle based on historical data and dynamically adjusts the minimum safe distance based on environmental parameters. This ensures both computational efficiency and improves the foresight and accuracy of collision avoidance decisions, enabling the safe distance to be increased in advance when environmental interference intensifies, thus reserving sufficient response time for the execution module.

[0019] 3. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion of the present invention constructs a distributed CAN bus network through a communication module, enabling the control modules of each tower crane to interact with status and risk data in real time as independent nodes, providing cross-device data support for collision avoidance decisions in multi-tower collaborative operation scenarios. The execution module accurately executes actions such as speed adjustment, power control, and early warning prompts according to control commands, transforming logical judgment results into operable safety protection behaviors. The entire system, while ensuring monitoring accuracy, improves the overall safety and stability of tower crane operation through modular architecture and efficient communication mechanisms. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of a tower crane anti-collision monitoring system based on CAN bus and multi-sensor fusion according to an embodiment of the present invention; Figure 2 This is a diagram illustrating the overall hardware architecture of an embodiment of the present invention. Figure 3 This is a distributed control topology diagram based on the CAN bus according to an embodiment of the present invention; Figure 4 This is a connection diagram of the functional modules of the DSP controller according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the sensor installation layout on a tower crane according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the control method according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0022] Example 1 Please refer to Figure 1 This embodiment 1 provides a tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion, including: A sensing module for collecting tower crane operating status data and external environment data; a control module for receiving sensor data output from the sensing module; a communication module for providing multi-tower collaborative data support for the control module's logical judgments; and an execution module for receiving control commands output from the control module and executing corresponding anti-collision actions according to the commands. The control module adopts a dual-controller collaborative architecture, including a digital signal processor (DSP) for driving control of the tower crane motor, and a logic controller (PLC) for sensor data acquisition, multi-sensor fusion collision avoidance method calculation, and collision risk logic judgment. The multi-sensor fusion collision avoidance method dynamically corrects the preset collision avoidance safety distance threshold based on environmental sensor data. The PLC controller also outputs control commands to the execution module and interacts with relevant data to the communication module.

[0023] To better understand this embodiment, the technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments. See also Figure 2 , Figure 3 , Figure 4 as well as Figure 5 : For the system architecture and communication network, this system adopts a distributed control architecture based on CAN bus. Each tower crane is equipped with an independent sub-control system, including a DSP driver module and a PLC logic module. All subsystems are connected to form a local area network via two signal lines, CANH and CANL.

[0024] In terms of communication mechanism, the CAN bus adopts an extended frame format, and the identifier (ID) includes a priority segment and a tower crane number segment. Alarm information has the highest priority, ensuring priority transmission even when the bus load is high. The CAN bus supports multi-master transmission, and any tower crane node can send an emergency stop or avoidance request to the bus with the highest priority when it detects a collision risk, with latency as low as milliseconds.

[0025] In terms of modular design, the system is divided into a host computer monitoring module (module 0) and various tower crane sub-control modules (modules 1~n). Module 0 is responsible for coordinating communication and caching data. Each sub-module independently executes the anti-collision strategy. Even if the host computer communication is interrupted, the sub-module can still achieve single-machine protection based on local sensor data.

[0026] This embodiment 1 further elaborates on the above modules.

[0027] (1) Perception module During tower crane operation, real-time monitoring of its operating status and surrounding environment is the foundation of collision avoidance safety. Traditional sensing methods suffer from problems such as single monitoring dimensions and incomplete data coverage, making it difficult to adapt to the collision avoidance requirements in complex operating scenarios. Therefore, the sensing layer of this system, namely the data acquisition module, has been specially constructed to build a comprehensive sensor network that includes the internal operating status of the tower crane and the external operating environment, realizing the collection of multi-dimensional data and providing reliable data support for subsequent collision avoidance logic calculations.

[0028] The perception layer, as the core of the entire collision avoidance monitoring system, completes the collection of different types of monitoring data through the scientific deployment and collaborative work of various sensors. Among them, the internal sensors are mainly used to monitor the operating status of the tower crane itself, including rotary encoders and weight sensors. The rotary encoder is installed on the slewing mechanism, and its core function is to detect the slewing angle of the boom and provide real-time feedback on the rotation position and attitude of the boom, so that the control module can determine the location of the boom. The weight sensor is installed at the fixed end of the hoisting rope to monitor the actual weight of the load, so as to keep track of the load status of the tower crane and provide data reference for preventing overloading and ensuring the stability of the tower body.

[0029] External sensors are primarily used to monitor the operating environment around the tower crane. These sensors include ultrasonic sensors, dual-axis tilt sensors, and wind speed sensors. Ultrasonic sensors, installed at the end of the boom, detect the distance between the tower crane and surrounding obstacles, promptly identifying potential collision risks. Dual-axis tilt sensors, installed on standard tower sections, are specifically designed to monitor tower stability, capturing the tower's tilt in real time and providing early warnings of potential overturning hazards caused by strong winds, overloading, or other factors. Wind speed sensors, installed at the top of the tower cap, monitor wind speed in real time, providing environmental parameters for dynamic adjustments to safety distances. These sensors work together, each fulfilling its specific function, to form a comprehensive, all-encompassing sensing system, ensuring comprehensive data collection and effectively addressing the shortcomings of traditional sensing methods.

[0030] For example, taking a specific configuration scheme as an example, in terms of sensor network layout and I / O configuration, the system integrates multiple sensors, which are uniformly collected and processed through the PLC's I / O interface. The specific configuration is as follows: The system uses an ultrasonic ranging sensor, model AR841 or HC-SR04, as the core component for external distance monitoring. It is installed at the front end of the tower crane boom and the trolley position. The sensor can detect the distance to obstacles in the tower crane's travel direction and working range. The collected distance data is connected to the PLC's analog input channel IW64. Through the transmission characteristics of the analog channel, the stable transmission of continuous distance signals is achieved.

[0031] The tilt sensor is model ADXL335 and is installed on the standard section of the tower crane. This sensor can monitor the tilt of the tower body on both axes in real time and reflect the attitude of the tower body in a timely manner. During operation, it can effectively warn of the tower body overturning hazards caused by overload or strong winds. The tilt angle signal it collects is connected to the digital input I0.4 of the PLC.

[0032] The weight sensor, model RSCC or HX711, is installed at the fixed end of the hoisting wire rope to measure the lifting weight of the tower crane. This allows for real-time monitoring of the equipment's load and helps prevent structural damage or safety accidents caused by overloading. The weight data collected by the sensor is connected to the PLC's analog channel IW66. By leveraging the adaptability of the analog channel, stable acquisition of lifting weight data is achieved, providing data support for equipment load management.

[0033] The wind speed sensor is an Anemometer model, installed in an unobstructed area on the top of the tower cap to ensure accurate monitoring of real-time wind speed in the working environment. This provides environmental parameters for dynamic correction of the safety distance. The wind speed signal it collects is connected to the PLC's digital input I0.5. Through the efficient transmission characteristics of digital input, timely acquisition of wind speed data is achieved, adapting to the dynamic monitoring needs of environmental parameters during tower crane operation.

[0034] Each sensor was selected and positioned according to its functional requirements. Data was categorized and accessed through different types of I / O channels of the PLC, which not only ensured the efficient acquisition of various types of sensor data, but also achieved the orderly transmission of data, providing a complete and reliable data foundation for subsequent multi-sensor fusion computing and collision avoidance decision-making.

[0035] (2) Control module At tower crane operation sites, high-frequency common-mode interference from equipment such as frequency converters and high-power motors exists. Meanwhile, the harsh outdoor environment and complex operating conditions place high demands on controller performance, data acquisition accuracy, and timely risk response. Therefore, the system's control module adopts a collaborative architecture of a DSP motion controller and a PLC logic controller, coupled with a three-level risk response mechanism and a multi-sensor fusion collision avoidance method to ensure tower crane operation safety.

[0036] As the core of motor drive and angle acquisition, the DSP motion controller integrates a quadrature encoder pulse (QEP) unit specifically for acquiring the boom slewing angle. This unit, configured in 4x frequency multiplication mode, can directly read the quadrature pulse signal output from the incremental rotary encoder to complete the acquisition of the boom slewing angle, providing angle data support for tower crane attitude control. Simultaneously, the DSP motion controller's PWM module generates complementary PWM waveforms to drive the intelligent power module, thereby achieving operational control of the tower crane motor and ensuring smooth execution of motor start-up, shutdown, speed adjustment, and other actions.

[0037] The PLC logic controller can be the Siemens S7-1200 series, or other industrial controllers with analog signal processing and differential signal input functions. The reason for choosing this type of controller is that it integrates two analog inputs and two analog outputs, and supports 1.5V differential signal input. This differential input characteristic, through differential amplification, effectively suppresses high-frequency common-mode interference generated by field frequency converters and high-power motors, ensuring the stability of sensor data transmission. At the same time, its operating temperature range is suitable for harsh outdoor environments, its protection level meets outdoor operation requirements, and it can adapt to complex working conditions on construction sites.

[0038] During operation, the PLC continuously receives various information collected by the sensing module, including the real-time relative distance between the tower crane and obstacles, ambient wind speed, and tower tilt angle. This data is updated at fixed time intervals. The PLC processes wind speed and tower tilt angle data from multiple consecutive collection cycles to obtain predicted values ​​for the next collection cycle, thus reflecting the changing trends of the environment and equipment attitude. Specifically, the PLC uses a multi-sensor fusion collision avoidance method to dynamically correct the preset collision avoidance safety distance threshold. Minimum safe distance for tower crane foundation when there is no environmental interference Set the critical wind speed value Critical value of tower tilt angle ; The sensing module collects data at a fixed cycle. Continuously collect real-time relative position and distance between the tower crane and obstacles Real-time wind speed values Real-time tilt angle of the tower ,in This is the current data collection time; Linear prediction calculations are performed on the wind speed values ​​from three consecutive data acquisition cycles to obtain the predicted wind speed value for the next data acquisition cycle. , Linear prediction calculations are performed on the tower tilt angle for three consecutive acquisition cycles to obtain the predicted tilt angle for the next acquisition cycle. , ; Wind speed correction factor is set based on predicted wind speed value. Set the tilt correction factor based on the predicted tilt angle. ,when hour It shows an increasing change, when hour It shows an increasing change, when hour For a fixed reference value, when hour For fixed reference values; By fusing the real-time relative position distance with correction factors for predicted environmental parameters, the real-time minimum safe distance for tower cranes is calculated. , ; The logic controller PLC will display the relative position and distance in real time. With real-time minimum safe distance Perform real-time comparisons and output corresponding anti-collision control commands to the execution module based on the comparison results; in, The wind speed value collected by the sensing module in the previous collection cycle. The tower tilt angle was collected by the sensing module in the previous data collection cycle. For the ultrasonic sensor in the sensing module The real-time relative position and distance between the tower crane and the obstacle are constantly monitored.

[0039] (3) Communication module When multiple tower cranes operate simultaneously on a construction site, each crane operates independently. Without an efficient data exchange mechanism, information gaps can easily lead to collisions. Therefore, the system's communication module employs a distributed communication network based on a CAN bus to establish data exchange channels between the tower cranes, ensuring information synchronization during collaborative operations.

[0040] This distributed communication network uses a CAN bus as its core architecture, with each tower crane's control module acting as an independent node connected to the CAN bus. Each node continuously transmits its own operational status data to the bus according to a unified communication protocol, while simultaneously receiving data from other nodes on the bus. The transmitted data includes key information such as real-time operating parameters of each tower crane and collision risk assessment results, enabling real-time information exchange between the tower cranes. This allows each tower crane's control module to promptly grasp the operational status of surrounding tower cranes, providing data support for multi-tower collaborative collision avoidance.

[0041] This distributed communication network adopts a decentralized multi-master communication mode, unlike centralized communication that relies on a host computer for forwarding. Each control node in the network has independent collision risk calculation capabilities, without relying on instructions from other nodes or the host computer monitoring module. When a control node detects an impending collision risk with another tower crane through its own sensing module and logical operations, that node has the authority to send a high-priority emergency braking frame to the CAN bus. After the emergency braking frame is sent, it can be directly received by other relevant nodes on the bus without being forwarded by the host computer monitoring module. Upon receiving the emergency braking frame, the relevant nodes promptly execute the corresponding anti-collision control actions, shortening the risk response time and preventing collision accidents. This decentralized multi-master communication mode ensures rapid response when a collision risk occurs, while reducing the impact of host computer failures on the entire communication system and guaranteeing communication reliability during multi-tower collaborative operations.

[0042] (4) Execution module In construction scenarios, tower cranes operate in complex environments, and relying solely on distance assessment is insufficient to meet the safety requirements of varying working conditions, easily leading to untimely protection. Based on existing hardware configurations, the system embeds a three-level risk response logic, dynamically adjusting protection strategies according to environmental parameters to form a complete safety control process. The specific process is as follows: The system's execution module consists of a frequency converter, contactors, and an audible and visual alarm. The frequency converter regulates the crane boom's operating speed, the contactors control the power supply to each mechanism, and the audible and visual alarm issues safety warnings. These hardware devices work together to provide fundamental support for risk response, ensuring that corresponding protective actions are executed under different risk levels.

[0043] The system's three-tiered risk response mechanism executes different preventative actions based on the level of risk, and dynamically adjusts response standards in conjunction with environmental parameters to avoid security vulnerabilities caused by fixed thresholds. When the obstacle distance is within the first preset range and the wind speed does not exceed the set standard, the system enters the early warning response level, activating the audible and visual alarm and displaying a prompt on the operating interface. At this time, the driver can operate the equipment normally and only needs to pay attention to changes in risk.

[0044] When the distance to an obstacle enters the second preset range, or when the ambient wind speed or tower tilt angle reaches a set threshold, the system enters an intervention-level response. At this time, the PLC controls the frequency converter to limit the operating speed of the crane boom within a specified range. Simultaneously, combined with environmental data collected by multiple sensors, it plans a reasonable avoidance path according to preset collision avoidance logic to prevent the equipment from colliding with obstacles and ensure operational safety.

[0045] When the distance to an obstacle is less than the minimum safe distance, or when environmental parameters exceed the limit threshold, the system enters a hazardous response phase. The PLC immediately controls the contactor to cut off the power to the corresponding mechanism and simultaneously performs a forced braking operation to stop the crane boom from moving in the hazardous direction. In addition, the system automatically records all sensor data for the 30 seconds prior to braking and stores it in non-volatile memory for subsequent troubleshooting and analysis.

[0046] To improve the accuracy of protection, the system dynamically adjusts the response threshold based on environmental parameters. When the wind speed sensor detects a value exceeding the set standard, the system will correspondingly increase the trigger distance of the intervention level to compensate for the safety hazards caused by the inertial swaying of the boom due to strong winds. When the tilt sensor detects an excessive rate of change in the tower's tilt, indicating severe load swaying, the system will further reduce the boom's operating speed to ensure the safety of the equipment structure.

[0047] The entire risk response process relies on the hardware support of the execution module and the preset logical rules to complete different levels of protection operations without manual intervention. This avoids the limitations of single distance judgment and makes the protection actions more in line with the actual operation scenario through dynamic correction of environmental parameters, thus ensuring the safe operation of tower cranes.

[0048] For example, a specific implementation configuration scheme will be used to illustrate this as follows: When the wind speed sensor detects a value exceeding 10 m / s, the system automatically adjusts the trigger distance threshold for the intervention stage from 5 m to 8 m to compensate for the inertial sway of the boom caused by strong winds. When the tilt sensor detects an excessive rate of change in the tower's tilt angle, the system reduces the speed limit for the intervention stage from 50% to 20% to maintain the stability of the equipment structure.

[0049] The system is divided into three risk response zones, with the triggering conditions and actions for each zone as follows. The warning level is triggered when obstacles are within 5 to 10 meters away, or when wind speed does not exceed 10 m / s. When these conditions are met, the system will display a pop-up notification on the HMI interface and simultaneously activate the audible and visual alarms. Operators can then continue with normal operations.

[0050] The intervention-level trigger conditions correspond to obstacle distances between 2m and 5m, wind speeds between 10m / s and 15m / s, or tower tilt angles between 3° and 5°. The collision avoidance logic in this stage employs either the dynamic potential field method or the minimum safe distance method. The determination of the minimum safe distance integrates wind speed correction factors and tilt angle correction factors. When the wind speed sensor reading exceeds 10m / s, the wind speed correction factor increases accordingly, allowing the system to trigger braking actions earlier at greater distances, achieving fusion decision-making based on multi-source sensing data. The PLC controls the frequency converter via analog output to limit the boom's movement speed to 50% and plans an avoidance path according to the potential field algorithm.

[0051] The triggering conditions for the hazardous level correspond to obstacles being less than 2m away, wind speeds greater than 15m / s, or tilt angles greater than 5°. When the conditions are met, the PLC immediately cuts off the power to the moving mechanism in the hazardous direction, performs emergency braking, and simultaneously records the sensor data for the 30 seconds prior to braking triggering into non-volatile memory.

[0052] Example 2 Please refer to Figure 6 This embodiment 2 provides a tower crane collision avoidance monitoring method based on CAN bus and multi-sensor fusion, applied to a tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion as described in any one of the embodiments, including: S1. The sensing module continuously collects the tower crane's operating status data and external environment data at a fixed collection cycle, including the real-time relative position distance between the tower crane and obstacles, the real-time wind speed value, and the real-time tilt angle of the tower body, and outputs the collected data to the control module. S2. Based on the collected data, the control module performs linear predictions on the wind speed and tower tilt angle for multiple consecutive collection cycles to obtain the predicted wind speed and tilt angle for the next collection cycle; based on the prediction results, wind speed correction factors and tilt angle correction factors are set and fused to obtain the real-time minimum safe distance. S3. The control module compares the real-time relative position distance with the real-time minimum safe distance, generates corresponding anti-collision control commands based on the comparison results, and outputs the control commands to the execution module. At the same time, the relevant operating status and risk data are exchanged with the control modules of other tower cranes through the communication module. S4. The execution module receives control commands and performs corresponding anti-collision actions, including adjusting the crane boom's running speed, controlling the power supply of the control mechanism, and issuing collision warning prompts.

[0053] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion, characterized in that, include: A sensing module used to collect operating status data and external environment data of tower cranes; A control module for receiving sensor data output from the sensing module; A communication module that provides multi-tower collaborative data support for the logic judgment of the control module; and an execution module that receives control commands output by the control module and executes corresponding anti-collision actions according to the commands. The control module adopts a dual-controller collaborative architecture, including a digital signal processor (DSP) for driving control of the tower crane motor, and a logic controller (PLC) for sensor data acquisition, multi-sensor fusion collision avoidance method calculation, and collision risk logic judgment. The multi-sensor fusion collision avoidance method dynamically corrects the preset collision avoidance safety distance threshold based on environmental sensor data. The PLC controller also outputs control commands to the execution module and interacts with relevant data to the communication module.

2. The tower crane anti-collision monitoring system based on CAN bus and multi-sensor fusion according to claim 1, characterized in that, The sensing module includes a rotary encoder for detecting the boom rotation angle, an ultrasonic sensor for detecting the distance to obstacles, a dual-axis tilt sensor for monitoring tower stability, a weight sensor for monitoring load weight, and a wind speed sensor for monitoring ambient wind speed. The rotary encoder is installed on the slewing mechanism, the ultrasonic sensor is installed at the end of the boom, the dual-axis tilt sensor is installed on the standard section of the tower body, the weight sensor is installed at the fixed end of the hoisting rope, and the wind speed sensor is installed at the top of the tower cap.

3. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion according to claim 1, characterized in that, The communication module is a distributed communication network based on the CAN bus. The control modules of each tower crane are mounted on the bus as independent nodes to complete real-time data exchange, including the operating status of the tower cranes and collision risks between the nodes.

4. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion according to claim 3, characterized in that, The distributed communication network adopts a decentralized multi-master communication mode: any control node in the network has the ability to independently calculate collision risks. When a node detects an impending collision risk, it has the authority to send the highest priority emergency braking frame to the bus, and this process does not depend on the forwarding of the host computer monitoring module.

5. A tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion as described in claim 1, characterized in that, The execution module includes a frequency converter for adjusting the operating speed of the crane boom, a contactor for controlling the power supply to the mechanism, and an audible and visual alarm for issuing collision warnings.

6. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion according to claim 1, characterized in that, The logic controller (PLC) receives signals from remote sensors through differential input ports and uses differential amplification principles to suppress high-frequency common-mode interference generated by field frequency converters and high-power motors.

7. The tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion according to claim 1, characterized in that, The collision avoidance monitoring system is equipped with a three-level risk response mechanism: Warning level: When the distance to an obstacle enters the first preset range, an audible and visual alarm is triggered; Intervention level: When the distance to an obstacle enters the second preset range, or when the ambient wind speed or tower tilt angle reaches a set threshold, the system limits the operating speed of the crane boom and plans an avoidance path based on a multi-sensor fusion collision avoidance method; Hazard level: When the distance to the obstacle is less than the minimum safe distance, or the environmental parameters exceed the limit threshold, immediately cut off the power supply to the mechanism moving in the dangerous direction and implement forced braking.

8. A tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion according to claim 1, characterized in that, The digital signal processor (DSP) integrates an orthogonal coded pulse (QEP) unit; the orthogonal coded pulse (QEP) unit is a pulse signal acquisition unit used to directly read the orthogonal pulse signals of the rotary encoder and to complete the high-precision acquisition of the slewing angle of the tower crane boom.

9. A tower crane anti-collision monitoring system based on CAN bus and multi-sensor fusion according to claim 1, characterized in that, The multi-sensor fusion collision avoidance method is specifically as follows: The minimum safe distance method is used for collision avoidance logic calculation, and the minimum safe distance of the tower crane foundation is preset when there is no environmental interference. Set the critical wind speed value Critical value of tower tilt angle ; The sensing module collects data at a fixed cycle. Continuously collect real-time relative position and distance between the tower crane and obstacles Real-time wind speed values Real-time tilt angle of the tower ,in This is the current data collection time; Linear prediction calculations are performed on the wind speed values ​​from three consecutive data acquisition cycles to obtain the predicted wind speed value for the next data acquisition cycle. , Linear prediction calculations are performed on the tower tilt angle for three consecutive acquisition cycles to obtain the predicted tilt angle for the next acquisition cycle. , ; Wind speed correction factor is set based on predicted wind speed value. Set the tilt correction factor based on the predicted tilt angle. ,when hour It shows an increasing change, when hour It shows an increasing change, when hour For a fixed reference value, when hour For fixed reference values; By fusing the real-time relative position distance with correction factors for predicted environmental parameters, the real-time minimum safe distance for tower cranes is calculated. , ; The logic controller PLC will display the relative position and distance in real time. With real-time minimum safe distance Perform real-time comparisons and output corresponding anti-collision control commands to the execution module based on the comparison results; in, The wind speed value collected by the sensing module in the previous collection cycle. The tower tilt angle was collected by the sensing module in the previous data collection cycle. For the ultrasonic sensor in the sensing module The real-time relative position and distance between the tower crane and the obstacle are constantly monitored.

10. A tower crane collision avoidance monitoring method based on CAN bus and multi-sensor fusion, applied to a tower crane collision avoidance monitoring system based on CAN bus and multi-sensor fusion as described in any one of claims 1-9, characterized in that, include: S1. The sensing module continuously collects the tower crane's operating status data and external environment data at a fixed collection cycle, including the real-time relative position distance between the tower crane and obstacles, the real-time wind speed value, and the real-time tilt angle of the tower body, and outputs the collected data to the control module. S2. Based on the collected data, the control module performs linear predictions on the wind speed and tower tilt angle for multiple consecutive collection cycles to obtain the predicted wind speed and tilt angle for the next collection cycle; based on the prediction results, wind speed correction factors and tilt angle correction factors are set and fused to obtain the real-time minimum safe distance. S3. The control module compares the real-time relative position distance with the real-time minimum safe distance, generates corresponding anti-collision control commands based on the comparison results, and outputs the control commands to the execution module. At the same time, the relevant operating status and risk data are exchanged with the control modules of other tower cranes through the communication module. S4. The execution module receives control commands and performs corresponding anti-collision actions, including adjusting the crane boom's running speed, controlling the power supply of the control mechanism, and issuing collision warning prompts.

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